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Generate a personalized daily health coaching message by dispatching 10 specialist subagents that each review the user's data from their domain expertise. Each subagent delivers its own message as a separate Telegram bubble.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | daily-coach |
| description | Generate a personalized daily health coaching message by dispatching 10 specialist subagents that each review the user's data from their domain expertise. Each subagent delivers its own message as a separate Telegram bubble. |
| user-invocable | false |
Use this skill when:
Call both tools to build the shared context payload:
coaching_context tool:{ }
nutrition tool for weekly summary:{
"command": "weekly_summary",
"end_date": "YYYY-MM-DD"
}
If insufficient_data is true: skip subagent dispatch. Instead say what is missing and what to log next.
Read each agent prompt file from {baseDir}/../../agents/ and spawn all 10 in parallel using sessions_spawn.
| # | File | Role | Emoji |
|---|---|---|---|
| 1 | imperial-physician.md | Orchestrator — #1 priority for today | 🏥 |
| 2 | diet-physician.md | Nutrition — meals, macros, micros | 🍚 |
| 3 | movement-master.md | Exercise — strain, training load | 🏃 |
| 4 | pulse-reader.md | Body metrics — RHR, HRV, SpO2 | 💓 |
| 5 | formula-tester.md | Cross-domain pattern detection | 🧪 |
| 6 | herbalist.md | Supplement considerations | 🌿 |
| 7 | trial-monitor.md | Experiment status + compliance | 📋 |
| 8 | court-magistrate.md | Trial design candidates | ⚖️ |
| 9 | medical-censor.md | Safety flags + warnings | 🛡️ |
| 10 | court-scribe.md | Relevant news + literature | 📜 |
For each agent in the registry:
read("{baseDir}/../../agents/{file}"){contents of the agent .md file}
---
TODAY'S CONTEXT:
{paste the full JSON context payload from Step 1}
WEEKLY NUTRITION:
{paste the weekly summary JSON from Step 1}
sessions_spawn(task=<constructed task>, label=<role name>)Spawn ALL 10 in parallel. Each subagent runs independently and announces its result back as a separate message.
Each subagent announces directly to the chat channel as a separate Telegram bubble. They arrive as each finishes. The main agent does NOT need to collect or reformat the results.
After all 10 have announced, if checkin_needed is true, send one final message prompting the user to log their experiment check-in.
[Role Emoji].The install script (step 6) configures agents.defaults.subagents.maxChildrenPerAgent and maxConcurrent to 10 in ~/.openclaw/openclaw.json. Without this, only 5 of the 10 specialists will spawn.
Meta-skill for the Turri bundle that routes natural language health conversations to the right capability — nutrition logging, health profile, pattern discovery, experiments, news, or daily coaching.
Log meals from food photos or natural language descriptions — infer ingredients, call the nutrition tool immediately, and return full micronutrient detail. Do not estimate nutrition in chat manually.
Answer health questions by routing to the most relevant specialist subagent(s) from the 10-agent roster, grounded in the user's own data.
Build and update a normalized personal health profile from Whoop data and natural conversation about goals, constraints, and preferences.
Discover patterns in health data, answer questions about correlations, and guide structured self-experiments with observation, hypothesis, check-ins, analysis, and next-step recommendations.
Fetch and summarize a curated daily digest of health, longevity, nutrition, sleep, exercise, and aging news from predefined sources.